Franchise vs individual establishment: The data is listed by individual establishment. For example, in the first 400 rows, there are 7 McDonalds (in PR).
Square footage: I double checked and didn’t find this. There is an Office Size Code column but it is empty.
Data also contains the percent of businesses in each municipality that are in each 2-digit NAICS classification. I did not visualize those for eac
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
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## ✓ tibble 3.0.4 ✓ dplyr 1.0.2
## ✓ tidyr 1.1.2 ✓ stringr 1.4.0
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## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(tidylog)
##
## Attaching package: 'tidylog'
## The following objects are masked from 'package:dplyr':
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## add_count, add_tally, anti_join, count, distinct, distinct_all,
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library(sf)
## Linking to GEOS 3.8.1, GDAL 3.1.1, PROJ 6.3.1
library(tmap)
bus_data <- read.csv("data_in_progress/nj_bus_mun.csv",
colClasses = c("SSN" = "character"))
mun <- st_read("data_in_progress/mun_boundaries.geojson") %>%
select(SSN)
## Reading layer `mun_boundaries' from data source `/Users/gabemorrison/Documents/U_Chicago_Year_4/NJ-opioidenv/data_in_progress/mun_boundaries.geojson' using driver `GeoJSON'
## Simple feature collection with 565 features and 6 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: 193684.7 ymin: 34954.71 xmax: 657059.7 ymax: 919556.3
## projected CRS: NAD83 / New Jersey (ftUS)
## select: dropped 5 variables (Place.Name, GNIS_NAME, GNIS, SQ_MILES, POP2010)
bus_data <- left_join(bus_data, mun) %>%
st_as_sf
## Joining, by = "SSN"
## left_join: added one column (geometry)
## > rows only in x 1
## > rows only in y ( 1)
## > matched rows 564
## > =====
## > rows total 565
col_names <- colnames(bus_data)
col_names <- col_names[-(1:2)]
col_names <- col_names[-97]
make_map <- function(col_name) {
tm_shape(bus_data) + tm_fill(col = col_name, style = "jenks") + tm_borders(alpha = .15)
}
maps <- lapply(col_names, make_map)
Takeaways: Generally small employment size near NYC; mean size increased slightly in rural areas, not a ton in urban NE and E.
maps[1]
## [[1]]
## Warning: The shape bus_data contains empty units.
maps[2]
## [[1]]
## Warning: The shape bus_data contains empty units.
maps[33]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[34]
## [[1]]
## Warning: The shape bus_data contains empty units.
maps[65]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Variable(s) "pct_change_mean_emp_size" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.62, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[66]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Variable(s) "pct_change_med_emp_size" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.59, 0.62, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
##Sales Volume:
Takeaways: Again relatively consistent patterns. Appears that sales volume was relatively consistent but went down in rural western side.
maps[3]
## [[1]]
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maps[4]
## [[1]]
maps[35]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.60, 0.55. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[36]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[67]
## [[1]]
## Variable(s) "pct_change_mean_sales_vol" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.59, 0.62, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[68]
## [[1]]
## Variable(s) "pct_change_med_sales_vol" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
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##Simpson Index Number of employees:
Relatively high diversity across the state. Not a lot of variability in the measures :(, so may not be great for modelling.
maps[5]
## [[1]]
## Legend labels were too wide. The labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[37]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[69]
## [[1]]
## Variable(s) "pct_change_simp_index_emp_size" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.59, 0.59, 0.62, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
##Business Counts:
Takeaway: Consistently more businesses where there are more people, even as those municipalities are smaller. These data don’t change a ton 2014-2018 (light yellow is close to no change).
maps[32]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.60. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[64]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.60. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[96]
## [[1]]
## Variable(s) "pct_change_all_bus" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.59, 0.59, 0.62, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
Not terribly successful; may need raw counts rather than percents
maps[18]
## [[1]]
## Legend labels were too wide. The labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[52]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[84]
## [[1]]
## Variable(s) "pct_change_pct_naics_2_54" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.59, 0.62, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
#NAICS 55- Management of Companies and Enterprises:
maps[21]
## [[1]]
## Legend labels were too wide. The labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[53]
## [[1]]
## Some legend labels were too wide. These labels have been resized to 0.55, 0.55, 0.55, 0.55, 0.55. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[85]
## [[1]]
## Variable(s) "pct_change_pct_naics_2_55" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
#NAICS 71- Arts, Entertainment, and Recreation:
maps[23]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Legend labels were too wide. The labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[57]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
maps[89]
## [[1]]
## Warning: The shape bus_data contains empty units.
## Variable(s) "pct_change_pct_naics_2_71" contains positive and negative values, so midpoint is set to 0. Set midpoint = NA to show the full spectrum of the color palette.
## Some legend labels were too wide. These labels have been resized to 0.65, 0.65, 0.65. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.